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Working with LLM"],"metadata":{"id":"B_SNEV0wxkpY"}},{"cell_type":"code","execution_count":null,"metadata":{"id":"grNbAtGzy5kD"},"outputs":[],"source":["!pip install transformers accelerate peft datasets bitsandbytes"]},{"cell_type":"code","source":["from transformers import BitsAndBytesConfig, AutoConfig,AutoModelForCausalLM, AutoTokenizer, pipeline\n","import torch"],"metadata":{"id":"Ngj26D4A19ZT"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["# bir alıntı\n","# This BitsAndBytes tool makes it possible to quantize our model,\n","# which in turn enables us to fit it onto a single A100 GPU. Without quantization,\n","#we would require over 8 A100s to achieve the same result.\n","\n","bnb_config = BitsAndBytesConfig(\n","    load_in_4bit=True,\n","    bnb_4bit_quant_type='nf4',\n","    bnb_4bit_use_double_quant=True,\n","    bnb_4bit_compute_dtype=torch.bfloat16\n",")"],"metadata":{"id":"82DDziSBz02Q"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["from huggingface_hub import login\n","access_token_read = \"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\"\n","login(token = access_token_read)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"NjFhjKe61sWw","executionInfo":{"status":"ok","timestamp":1695403708426,"user_tz":-180,"elapsed":644,"user":{"displayName":"Savas Yıldırım","userId":"10717726124681851716"}},"outputId":"cc64dae6-1ced-41d5-f9bd-da5e4f26fb1d"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Token will not been saved to git credential helper. Pass `add_to_git_credential=True` if you want to set the git credential as well.\n","Token is valid (permission: read).\n","Your token has been saved to /root/.cache/huggingface/token\n","Login successful\n"]}]},{"cell_type":"code","source":["#model_id = 'meta-llama/Llama-2-7b-hf'\n","model_path=\"meta-llama/Llama-2-7b-chat-hf\"\n","model = AutoModelForCausalLM.from_pretrained(\n","    model_path,\n","    trust_remote_code=True,\n","    quantization_config=bnb_config,\n","    device_map='auto',\n",")\n","model.eval()"],"metadata":{"id":"qP78LgUw15XC"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["tokenizer = AutoTokenizer.from_pretrained(\n","  model_path\n",")"],"metadata":{"id":"l_XWYbE-2L0Z"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["my_llama = pipeline(\n","    model=model,\n","    tokenizer=tokenizer,\n","    task=\"text-generation\",\n","    return_full_text=False,\n","    max_new_tokens=64,\n","    repetition_penalty=1.5\n","    )\n","\n","# max_new_tokens (int, optional) — The maximum numbers of tokens to generate, ignoring the number of tokens in the prompt\n","#num_beams (int, optional, defaults to 1) — Number of beams for beam search. 1 means no beam search.\n","#temperature (float, optional, defaults to 1.0) — The value used to modulate the next token probabilities.\n","# https://huggingface.co/docs/transformers/main_classes/text_generation\n","# repetition_penalty – (optional) float The parameter for repetition penalty. Between 1.0 and infinity. 1.0 means no penalty. Default to 1.0."],"metadata":{"id":"37p_iLhu4Aki"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":[],"metadata":{"id":"D1eYOeYcOvEG"}},{"cell_type":"code","source":["# '<s>[INST] <<SYS>>\\nYou are a helpful AI assistant. Reply your answer in mardkown format.\\n<</SYS>>\\n\\nWho directed The Dark Knight? [/INST] The director of The Dark Knight is Christopher Nolan. </s><s>[INST] What are the other movies he directed? [/INST]'"],"metadata":{"id":"EB0UB3J4OzPq"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["Q=\" What is the age/gender/race of the Subject ?\"\n","\n","Prompt=    '''\n","    <s> [INST]\n","    <<SYS>>\n","    You are Healthcare AI Information Extraction Assistant.\n","    Provide the answer in python dictionary format keeping it as short as possible .\\n\n","    <</SYS>>\n","   Context: A 52-year-old Black woman on phenytoin therapy for post-traumatic epilepsy developed transient hemiparesis contralateral to the injury ?\n","   Question: For given Context above. '''+Q+''' ?\n","[/INST]\n","'''\n","\n","#Prompt=\"What is the fable involving a fox and grapes?\"\n","\n","sequences = my_llama(\n","   Prompt,\n","    do_sample=True,\n","    num_return_sequences=1,\n","    #temperature=0.6,\n","    eos_token_id=tokenizer.eos_token_id,\n",")\n","\n","\n","for s in sequences:\n","  print(\"*\"*70)\n","  print(s['generated_text'])"],"metadata":{"id":"aEIAMrnR4-YR","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1695404543058,"user_tz":-180,"elapsed":2720,"user":{"displayName":"Savas Yıldırım","userId":"10717726124681851716"}},"outputId":"5f1c47b4-0fd8-4e62-be37-634dad7fe60d"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["**********************************************************************\n","{ \"Age\": 35, \"Gender\": \"Male\", \"Race\": \"Black\" }\n"]}]},{"cell_type":"code","source":["from datasets import load_dataset\n","dataset = load_dataset(\"ncbi_disease\")"],"metadata":{"id":"UjykJYFfzo8E","colab":{"base_uri":"https://localhost:8080/","height":369,"referenced_widgets":["9fb513f7f41f44fda2bfe19af7b68376","63058f7ef0b04c348d2f5412d8875730","79a8db64feab4eda8b8875cd67603731","43be27253a224501b91496f08b019180","e6c2cc4a373f4e3f8bb35a4afe5d65e6","a6dde5e76cc64e0ab60cee5cf2dee60d","b58c718df55f4333b8d96433ecadf2dd","f206d148ff004d8ea504357563bf8b79","276ce124243b47f28fde0140fca786d6","aac1e73613bc4b219d91d92d9b69703e","32050b5d4a9e4d188df929c0f6200590","f1749807ecc54173a6df6c2161907c37","ae7f424b22ad493db792a9bea0f94b8e","681c4feb74b947ad882e94416144fbc4","af10991d05fc45279975e034915e21b3","8462eb498eb24539828b9c15ef10d1d2","fe6fe97095cd49759ac0d91a7b7d9ef3","063d243ceca34ea9b76ab66e52c9e15e","3dfc5adcf4d44f1f9b69fec2c3561e7c","d3260f95a8ac496e8a6036966ae5a09c","a966a07b0fa44bab971e9f1c31fcf10d","2f3628e2b19b4e709f3044798023bf58","5d208241f92a4a5d83f99fb916d7d345","9bcd199e00604a3eaa1e86917280b8a7","4ff31cdede614874bcf8dfafb45ee2c3","681711ec1ef04526bcf4dcf2b0fbd4fb","b4a8760e55b248379c665064902dbbf0","0ad30decda0d4014a80dc0988cbc4d54","f18da8f9fbdd4e23975f2b3acfc27304","6f08d1afd06f4b22b477258d6ca6a33a","fc1833d5ed7b4d83a4d6538d37a0bd8f","14fd52ef279b4595a3dd594d01de4cdc","a46ff22624da4b5dbf61ec1767a45a28","cf40926e51bb49cc8e4db65978ad6e42","b6d60bfa85b349318d6ef9a19c5b7803","c1b962b357674f82bf1339d7162cc17f","f9083b5e9ffb43b898e949645b11ff47","5cf135d6711946d0a4e78c60945bdd5c","94b5013ac8684f6e9a10953deac88819","3dff157655ad46e58e827edc2d33c9cc","6621066c0dae4f52a40ea78b68731056","ec6f57d23e2c4a12854cb726707d90a7","55d7da60a7e1495d9c2c3b326628c432","2af21e6d9c6340299d5bc8fcd253c4f5","009d2a3bcb304b9494e9a070b5e8a33a","3cce7ce7a42942cd8afd4c574426370d","b7b80ad8bf7547beb147bbce52be76b7","9db21d343ce548a2ac1d9565f0ab2c12","6cf66c0ec11f46b6af20c3faa5c2489c","6fe4ea70c44244b38b3c70eae2872d01","c0613503361d432fb162818c73e324c8","1417f98db8a34a73be2996a415b68a41","4c7744b0c20549d78f9fb0f6c4e62405","da68088f32be481a86a88095d969be0e","22b099aec1624ebca3a90286c58c2550","54654e5c7f944865bef782b10d8a7729","2b188d59ed314bfca2c5bd3af8d12546","6b4e1015b8c64afb923f362d5f6fe342","f4844de96da843f381dbae1499940b82","1aa1b6e05e30498580859a676ff32ed6","37f0fe33c1074b12be08db5bc1c10df3","bf820d2021c243199a92ecc32b117496","0b9686f39d404dc6968ec85ac17296f6","f2d8c97135a7428aa553f03f0daaf990","657e99fca922468597d8ea23dd2c0ea8","9082d69488f64a35843853ddd3f20ecf","5bbe5d882c5f473697621c2daeffb913","122f4f37baf043139c48ba05aa1e566a","edaa6c9020a840d183c78129c4369c74","d22cbf40b4ff4e69add1b487353167be","0a2d7cca9b2046a5a0233a2884b6ea86","371deea9d90d44a6b585006ad3f0e6e8","6f972d2995b946d7a3c7851caf9e402c","79178599c7ad4982b886950dc20fd31b","1e35a3fe19a341e3b8d0d9e5b1be316f","11794348caf44dbbbcf46f5ba41c288c","bcf0268a2b734ddcb387365fd7787ba4","657563e4a3704f10b734c592e34b742b","53d1150512454ca89d76c2af03fd00fc","67c6f8a31ede419aa453ea615b8b05d8","ac81900b8aad48f89fd49f00a929ffe9","ab6f755e7c24443c860a4f51df75d194","c24fc671916e45f690304e69ac7e5106","19f39166c9e84fc5852c26055f595172","ab631884dd134077885f6543a9134c10","23913439cebf45b38a4e38f4dff4d147","75a29e4748ed4a07b832a6834da75313","d412501ac7fc4a87be90c6e52942d1ec","e7eb389c8f2540a7a848640516f596cf","b892226bb53b492ab6f12cc6d0ff5e8c","24091cdb18324c22a6bfe8d0fc3b0b3a","8848d3d2c9cb4bb7a6613cdf520e1b65","c272463db0294148ac55a12e4ead0b18","9e61b9da09b649a0bb24364bef972885","30c998b64dbd4f2e9a4bbc60ebf0f98c","0df6ce65f73c43468df13507ee960036","5240337b8c714a968d1b4b230c24107e","9e083b4ee6694652aa6db0fcafef50dc","d078851d3ce6445abdd1318bfe858c3f","f6b4ffe1e8a74aef81528778b4be7d0d","36a6280fc94348eaad6423ac62b339d0","6335710f45ba48079b4861cb5a7813c6","2e4ab37714ff4301a4505943b2524099","843544b0fc1c42d7a165a9b065181000","05ba6143c3f64892bef659a57a89dc76","c926325b19694522bdca4f989e879324","4ec581a5933b47028fb3ef636d876197","6cca09fb3357414a99a23a665ca83fdc","cc30d00baac64959982af5284660945e","9b916afd4dd54ecab72febecd3ff5357","07ab1221279d4217bf9102783bd5dfb8","eecd39df70e8489e9556ec9e832a3a36","c9d078c577fe4899aab4e8e8389f02ec","f8b97f05615240378c2ecb45220bc62b","07262b432c734ddeb587c74542f39a7b","e58abbb4f63a4e0a8160ee30035b3bf9","f51b47b4be2b4096878186faf70a5e6f","fc15c5a9fb914b42b21f94e32abae625","826a883b226a4267b47f4a2ff2947fa4","b036886eac484f23ada3e8937a4138e4","7bf1332e79024e798ab289c5270bc2a6"]},"executionInfo":{"status":"ok","timestamp":1695405517877,"user_tz":-180,"elapsed":9459,"user":{"displayName":"Savas Yıldırım","userId":"10717726124681851716"}},"outputId":"c11f9566-9fe6-424a-e548-bbab387cb811"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["Downloading builder script:   0%|          | 0.00/5.83k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"9fb513f7f41f44fda2bfe19af7b68376"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading metadata:   0%|          | 0.00/3.45k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"f1749807ecc54173a6df6c2161907c37"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading readme:   0%|          | 0.00/9.70k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"5d208241f92a4a5d83f99fb916d7d345"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Downloading data 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examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"f6b4ffe1e8a74aef81528778b4be7d0d"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Generating test split:   0%|          | 0/941 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"07ab1221279d4217bf9102783bd5dfb8"}},"metadata":{}}]},{"cell_type":"code","source":["import pandas as pd\n","pd.DataFrame(dataset)\n"],"metadata":{"id":"Js34aEggCwTy"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":[],"metadata":{"id":"-u2R4j1dC2ll"},"execution_count":null,"outputs":[]}]}